Interpretive Summary: Invasions by exotic plant species can generally be described with a logistic growth curve divided into three phases: introduction, expansion and saturation. This model is constructed primarily from regional studies of plant invasions based on historical records and herbarium samples. The goal of this study was to compare invasion curves at the site scale to the predicted logistic growth curve using long-term datasets that documented exotic weed invasions. Five datasets ranging from 41-86 years in length were recovered from five sites in four western states. Data for the following seven exotic species were analyzed using regression analysis to evaluate goodness of fit to a logistic curve: crested wheatgrass, cheatgrass, lehman lovegrass, desert madwort, saltlover, russian thistle and tall tumble mustard. Of these species, six increased in abundance over time in at least one location and five had R2 > 0.90 when fitted to a logistic curve. All other species/location combinations were characterized by sporadic spikes and crashes. One species that increased over time (lehman lovegrass) did not exhibit a lag phase at all, suggesting that in some cases, seedbank analysis may be a better predictor for invasion risk by exotic plants. Exotic forage species selected for their suitability to their respective regions exhibited medium and long introduction phases, suggesting that colonization processes are at least as important as evolutionary processes during invasion. We conclude that long-term datasets are an under-utilized tool that may provide invaluable information for studying the invasion process of exotic plants.

Technical Abstract:
Invasions by exotic species are generally described with a logistic growth curve divided into three phases: introduction, expansion and saturation. This model is constructed primarily from regional studies of plant invasions based on historical records and herbarium samples. The goal of this study was to compare invasion curves at the site scale to the logistic growth curve using long-term datasets. A search was conducted for long-term datasets that documented exotic weed invasions. Five datasets ranging 41-86 years in length were recovered from five sites in four western states. Data for the following seven exotic species were analyzed using regression analysis to evaluate fit to a logistic curve: Agropyron cristatum, Alyssum desertorum, Bromus tectorum, Eragrostis lehmanniana, Halogeton glomeratus, Salsola tragus and Sysimbrium altissimum. Of these species, six increased in abundance over time in at least one location and five had R2 > 0.90 when fitted to a logistic curve. All other species/location combinations were characterized by sporadic spikes and crashes. One species that increased over time (E. lehmanniana) did not exhibit lag phases at all, suggesting that in some cases, seedbank analysis may be a better predictor for invasion risk. Exotic forage species selected for their suitability to their respective regions exhibited medium and long introduction phases, suggesting that colonization processes are at least as important as evolutionary processes during invasion. We conclude that long-term datasets are an under-utilized tool that may provide invaluable information for studying the invasion process of exotic plants.